Sampled-based adaptive event-triggered resilient control for multiagent systems with hybrid cyber-attacks

计算机科学 服务拒绝攻击 多智能体系统 分布式计算 控制器(灌溉) 欺骗 事件(粒子物理) 控制(管理) 计算机安全 人工智能 互联网 物理 万维网 农学 生物 社会心理学 量子力学 心理学
作者
Tan Lihua,Xin Wang
出处
期刊:Neural Networks [Elsevier]
卷期号:172: 106090-106090 被引量:5
标识
DOI:10.1016/j.neunet.2023.12.044
摘要

The multiagent systems have shared broad application in many practical systems including unmanned aircraft clusters, intelligent robots, and intelligent transportation. However, many unexpected cyber-attacks may disturb or disrupt the normal communication of the agents, thus reducing the interacting efficiency of multiagent systems. Ever since the cyber-attacks have been proposed, the resilient control problem for multiagent systems has been intensively explored in light of the communication network growth. However, most of the consequences only focused on denial-of-service (DoS) attacks or deception attacks independently. Distinguished from the existing resilient control mechanisms, the current investigation represents the first attempt at designing an adaptive resilient controller for multiagent systems according to the sampled-based adaptive event-triggered manner, where denial-of-service (DoS) attacks and deception attacks are both considered. First, the hybrid cyber-attacks model and its impact on the closed-loop system are addressed. And then, an adaptive event-triggered strategy is proposed to reduce network resource consumption and ease the communication burden, where the designed adaptive law can automatically adjust the triggering threshold. Finally, the consensus state of multiagent systems is capable of achieving via a series of reasonable control rules formulated through Lyapunov functional approach despite suffering hybrid cyber-attacks. And a simulation example is given to substantiate the feasibility of the proposed method.
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